Review of Python Courses (Part 21)

In Part 20, I summarized my Datacamp courses 59-61. Today I will continue with the next three.

As a reminder, I introduced you to my recent work learning Python here.

My course #62 was Time Series Analysis in Python. This clearly has potential applications for investment returns, but in the end I wasn’t totally sure what those might be. The course covers:

• Introduction to the course
• Correlation of two time series
• Simple linear regressions (in statsmodels, numpy, pandas, scipy)
• Autocorrelation (convert index to datetime)
• Autocorrelation function (from statsmodels.graphics.tsaplots import plot_acf; from statsmodels.tsa.stattools import acf)
• White noise
• Random walk (from statsmodels.tsa.stattools import adfuller)
• Stationarity
• Introducing an AR model (from statsmodels.tsa.arima_process import ArmaProcess)
• Estimating and forecasting an AR model
• Choosing the right model (from statsmodels.graphics.tsaplots import plot_pacf)
• Estimation and forecasting an MA model
• ARMA models
• Cointegration models
• Case study: climate change

My course #63 was Intermediate Predictive Analytics in Python. This course covers:

• The basetable timeline
• The population
• The target
• Adding predictive variables
• Adding aggregated variables
• Adding evolutions
• Using evolution variables
• Creating dummies (avoiding multicollinearity)
• Missing values (list comprehension)
• Handling outliers (from scipy.stats.mstats import winsorize)
• Transformations
• Seasonality
• Using multiple snapshots
• The timegap

My course #64 was Building and Distributing Packages with Conda. This is another shell-related course I found hard to absorb since I do very little in the shell. I’m not the only newbie who feels this way, either. This was a recent post to the group:

> I have been doing Python courses for a while but now I actually wanna try some real
> live data on my laptop and I am not sure on how to install all of the needed stuff
> (pandas, numpy, etc.). I have downloaded the latest Python version and the PyCharm
> editor but… [the courses] do not really have anything to show you how to actually
> make the rest of the things work for inexperienced people such as myself.

I downloaded Spyder IDE, which has met most of my needs. It crashes sometimes and gives repetitive errors upon start-up, though, which are both quite annoying. I’ve also had mixed results downloading some libraries like Backtester.

Speaking of Anaconda, or conda for short, my 64th course covers:

• Anaconda Project
• Anaconda Project specification file
• Anaconda Project commands
• Python module and packages
• Python package directory
• Conda packages
• Conda package dependencies

I will review more courses next time.